Three agricultural regions of France: Three types of pluriactivity

In France, the new Common Agricultural Policy will have different regional impacts. There are three types of regions based on agricultural development. The first type is where farms are able to carry on a modernization process; the second type where farms are threatened in spite of their modernization, and the third type where farms are unable to be modernized. These three types of regions are represented in France by Picardy, Languedoc and Savoy. Each region is developing a particular form of pluriactivity in accordance with its own agricultural development. Picardy is setting up a business pluriactivity which uses agricultural resources to increase non-agricultural activities. Languedoc undergoes a rural development pluriactivity by using non-agricultural resources for its modernization. Savoy represents a rural pluriactivity of survival, in which the close combination between agricultural and non-agricultural activities permits the maintenance of rural many-faceted businesses.The three kinds of pluriactivity are very unlike. They show that, in France, agricultural development will in future be linked to rural development to a far greater extent.     

Estimation of period-specific gross migration flows from limited data: Bi-proportional adjustment approach

Two models, hierarchical in terms of input data requirements, are proposed to estimate place-to-place gross migration flows during a specified time period. In the first, the input data required are lifetime migration flows and the marginal totals of period migration, usually available from national censuses. The estimational algorithm is a ‘bi-proportional adjustment’ technique (and its variant) that assumes structural similarity between lifetime and period migration flows. The second model is designed to account for possible structural deviations in recent migratory patterns. Calibration of the procedure to replicate Indian and Korean data confirms high validity of estimation.     

Optimum stratification with two variates

For the 2×2 rectilinear stratification of a bivariate normal distribution with proportional and optimum allocation the dependence of the objective function z(x₁;y₁) on the coefficient of correlation ρ and the sampling fraction q=n/N is investigated. With proportional allocation for great values of ρ (but already for q=0) a so-called ρ-effect arises, which results in a saddle-point of z as “optimum” stratification point in the center of gravity of the distribution and two additional minima. With optimum allocation first for smaller values of q also the ρ-effect arises; for grater values of q a so-called q-effect is superposed, which results in a multitude of minima, saddle-points and maxima of z. All these points satisfy the generalized conditions of Dalenius, but for practical use only the global minimum is of interest.     

Naming the Beast: Defining and Classifying Service Innovations in Social Policy

Over the last decade, the search for innovationhas become a core component of much social policyformulation and implementation. This search, however,has often been undertaken with little attempt to define the actual nature of innovation or to classifyits different modes. This paper reports recent researchwhich has developed a typologyof organizational changewithin which to situate and analyze innovation in social policy. It argues that thistypologyis an essential tool both for socialpolicymakers and for those concerned with itsanalysis.     

Hook‐Ups and Train Wrecks: Contextual Parameters and the Coordination of Jazz Interactions

This article discusses the importance of several parameters of context integral to jazz musicians' ability to hear musical signs as meaningful, such as performers' individual backgrounds and the various other styles of music available in the aural landscape, and how those parameters influence what the musicians play. Several examples from an ongoing ethnography of jazz jam sessions suggest that context is constituted by several variables, that different variables may become salient at different times, and that different interactants vary in their ability to attend to these variables. This study thus extends and elaborates frame analysis by showing that, while an interaction frame of the sort described by Goffman (1974) may perdure, it is subject to change, and the nature of the context it provides for interactions can change whenever a new interaction is initiated.     

On the trimmed mean and minimax-variance L-estimation in Kolmogorov neighbourhoods

We consider the properties of the trimmed mean, as regards minimax-variance L-estimation of a location parameter in a Kolmogorov neighbourhood K() of the normal distribution: We first review some results on the search for an L-minimax estimator in this neighbourhood, i.e. a linear combination of order statistics whose maximum variance in K_t() is a minimum in the class of L-estimators. The natural candidate – the L-estimate which is efficient for that member of K_t,() with minimum Fisher information – is known not to be a saddlepoint solution to the minimax problem. We show here that it is not a solution at all. We do this by showing that a smaller maximum variance is attained by an appropriately trimmed mean. We argue that this trimmed mean, as well as being computationally simple – much simpler than the efficient L-estimate referred to above, and simpler than the minimax M- and R-estimators – is at least “nearly” minimax.